Predicting soil compaction parameters in expansive soils using advanced machine learning models: a comparative study by Sultan Almuaythir, Muhammad Syamsul Imran Zaini, Rida Hameed Lodhi

“…Detailed performance metrics, including correlation coefficients (r), mean absolute error (MAE), root mean squared error (RMSE), relative root mean squared error (RRMSE), and performance index (PI), were analyzed for each model across the training, testing, and validation datasets. …”
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Analysis of demand forecasting for Madura herbal medicine Rapet Wangi (Case study: PT. Firdaus Kurnia Indah) by Asfan Dian Farida, Ghooniyah Indriana Mahrotul, Maflahah Iffan

“…The smallest MAPE value indicates that the forecasting error is small. The results of this research, it can be concluded that considering the data on the quantity of raw materials at PT Firdaus Kurnia Indah, the exponential smoothing method is suitable for predicting rapet wangi’s product. …”
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Evaluation of Allele Frequency Estimation Using Pooled Sequencing Data Simulation by Yan Guo, David C. Samuels, Jiang Li, Travis Clark, Chung-I Li, Yu Shyr

“…Next-generation sequencing (NGS) technology has provided researchers with opportunities to study the genome in unprecedented detail. …”
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FUTURE TRENDS IN MILK FAT CONTENT: A FIVE-YEAR FORECAST FOR ROMANIA AND THE EUROPEAN UNION by Raluca-Aniela GHEORGHE-IRIMIA, Dana TĂPĂLOAGĂ, Cosmin ȘONEA, Paul-Rodian TĂPĂLOAGĂ, Silviu-Ionuț BEIA

“…The findings from the research conducted in Romania indicate a consistent albeit moderate increase in milk fat content. …”
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A Hybrid Spatial–Temporal Deep Learning Method for Metro Tunnel Displacement Prediction Under “Dual Carbon” Background by Jianyong Chai, Limin Jia, Jianfeng Liu, Enguang Hou, Zhe Chen

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Comparative Analysis of Machine Learning Techniques for Prediction of the Compressive Strength of Field Concrete by Omobolaji Opafola, Abisola Olayiwola, Ositola Osifeko, Adekunle David, Ajibola Oyedejı

“…The developed GB model achieved R-squared values of 91.60%, 91.43%, and 90.18% for the 10-fold, 5-fold, and 3-fold cross-validations, respectively, with mean absolute error, root mean squared error, and mean absolute percentage error values of 2.6776, 4.3523, and 9.19%, respectively. …”
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Analysis of photoneutron cross section accuracy obtained at quasimonochromatic gamma-beams by V. M. Mazur, Z. M. Bigan, P. S. Derechkey, I. Yu. Seyka, V. V. Grinyov, S. I. Luchkan

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Constacyclic codes over 𝔽q𝒮𝒯 and their applications by Amal S. Alali, Mohd Azmi, Nadeem ur Rehman, Mohammad Fareed Ahmad

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A review on label cleaning techniques for learning with noisy labels by Jongmin Shin, Jonghyeon Won, Hyun-Suk Lee, Jang-Won Lee

“…In practice, however, labels can be corrupted by human error or mistakes, known as label noise, which degrades classification accuracy. …”
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Solar Energy Datasets of Deep Learning Models Incorporating with GK-2A and ASOS Ground Measurements by Jong-Sung Ha, Seungtaek Jeong, Seyun Min, Yejin Lee, Suhwan Kim, Doehee Han, Jong-Min Yeom

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Interpretable machine learning approach to predict Hepatitis C virus NS5B inhibitor activity using voting-based LightGBM and SHAP by Teuku Rizky Noviandy, Aga Maulana, Irvanizam Irvanizam, Ghazi Mauer Idroes, Nur Balqis Maulydia, Trina Ekawati Tallei, Muhammad Subianto, Rinaldi Idroes

“…Our model achieves an R-squared (R2) value of 0.760, indicating strong predictive capability, along with a root mean squared error (RMSE) of 0.637, a mean absolute error (MAE) of 0.456, and a Pearson correlation coefficient (PCC) of 0.872, demonstrating the model's precision in predicting inhibitor potency and its strong linear correlation with experimental values. …”
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Petrological controls on the engineering properties of carbonate aggregates through a machine learning approach by Javid Hussain, Tehseen Zafar, Xiaodong Fu, Nafees Ali, Jian Chen, Fabrizio Frontalini, Jabir Hussain, Xiao Lina, George Kontakiotis, Olga Koumoutsakou

“…The main aim of this research is to assess the impact of petrographic characteristics on the engineering properties of carbonate rocks. …”
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UHF Partial Discharge Localization Methodology Based on Generalized Regression Neural Network by Qichen YU, Lingen LUO, Fan WU, Gehao SHENG, Xiuchen JIANG

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The Estimating Parameter and Number of Knots for Nonparametric Regression Methods in Modelling Time Series Data by Autcha Araveeporn

“…This research aims to explore and compare several nonparametric regression techniques, including smoothing splines, natural cubic splines, B-splines, and penalized spline methods. …”
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Next-Gen Decoding: Non-Binary LDPC Algorithms for Emerging Power Line and Visible Light Communications by Waheed Ullah, Fengfan Yang, Kwonhue Choi, Dushantha Nalin K. Jayakody

“…The review also highlights challenges and open research directions in non-binary LDPC decoding, such as mitigating error floors, reducing decoding complexity, and integrating with emerging communication technologies. …”
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CAGFNet: A Cross-Attention Image-Guided Fusion Network for Disparity Estimation of High-Resolution Satellite Stereo Images by Qian Zhang, Jia Ge, Shufang Tian, Laidian Xi

“…Experiments on the US3D dataset demonstrate State-of-the-Art performance, achieving an endpoint error (EPE) of 1.466 pixels (14.71% D1-error) on the Jacksonville subset and 0.996 pixels (10.53% D1-error) on the Omaha subset. …”
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Automatic serving method of volleyball training robot based on improved YOLOv5 and improved Hough transform by Tao Sun, Xiaolong He, Jiajun Zhang

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IDCC-SAM: A Zero-Shot Approach for Cell Counting in Immunocytochemistry Dataset Using the Segment Anything Model by Samuel Fanijo, Ali Jannesari, Julie Dickerson

“…Cell counting in immunocytochemistry is vital for biomedical research, supporting the diagnosis and treatment of diseases such as neurological disorders, autoimmune conditions, and cancer. …”
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Optimal pilot pattern for data‐aided channel estimation for MIMO‐OFDM wireless systems by Inaamullah Khan, Michael Cheffena

“…Abstract This article presents an optimal pilot pattern for the data‐aided channel estimation (DACE) scheme for both single‐input single‐output (SISO) and multiple‐input multiple‐output orthogonal frequency division multiplexing (MIMO‐OFDM) wireless systems. The research evaluates the performance of the DACE scheme using different comb‐type pilot patterns for both least square (LS) and linear minimum mean square error (LMMSE) channel estimators. …”
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Estimation of Infiltration Coefficients Based on the Average Infiltration Opportunity Time of the Advance Phase by Amin Seyedzadeh, Amir Panahi, Eisa Maroufpoor

“…The results showed that the advanced relationships obtained from the TR method have higher accuracy than the EW method. The average relative error index of the infiltration depth indicated that the infiltration relations obtained from the TR method with an average relative error of 2.4% is more accurate than the EW method.…”
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